As Ben explained to me at one point, too, it's not entirely clear that
throwing away the false convergences is a perfect solution. It seems
unlikely that the true parameters of a model that 'happens' not to converge
are a representative sample of the range of those parameters...
Daniel

On Thu, Feb 5, 2009 at 12:19 PM, Ben Bolker <bolker@ufl.edu> wrote:

>
>  I'm interested in the answer as well.  I thought about this
> briefly,  but the only thing I came up with (which is a terrible
> hack) is to use options(warn=2) to turn warnings into errors and
> then use try() to catch and evaluate the errors.  One might
> also be able to inspect last.warning ... There must
> be a better way though ...
>
>  Ben Bolker
>
> Hervé CHAPUIS wrote:
> > Hi everyone,
> >
> > I am using lmer (and glmer) in a simulation study in order to find the
> > best experimental design.
> > Using gaussian deviates I simulate a population and  I analyse the data
> > with a mixed model.
> > I repeat these operations many times (about 5000 replicates)  in order
> > to derive trends and distributions of parameters.
> >
> > My problem is that  I sometimes run into false convergences. I have a
> > warning message but that's all.
> > "Il y a eu 50 avis ou plus (utilisez warnings() pour voir les 50
> premiers)"
> >
> > Is there a way to obtain the convergence status of the lmer/glmer models
> > in a tractable way so that I  do not account for this replicate in case
> > of false  convergence ? Given the large number of replicates, I do not
> > run the program interactively.
> >
> > I hope I made it clear.
> > Many thanks.
> >
>
>
> --
> Ben Bolker
> Associate professor, Biology Dep't, Univ. of Florida
> bolker@ufl.edu / www.zoology.ufl.edu/bolker
> GPG key: www.zoology.ufl.edu/bolker/benbolker-publickey.asc
>
>
>
> --
> Ben Bolker
> Associate professor, Biology Dep't, Univ. of Florida
> bolker@ufl.edu / www.zoology.ufl.edu/bolker
> GPG key: www.zoology.ufl.edu/bolker/benbolker-publickey.asc
>
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>

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